Best Enterprise Data Science and Machine Learning Platforms - Page 2

How Many Data Science and Machine Learning Platforms Products Does G2 Track?

Total Products under this Category: 1,682

Category Stats (Sep 2026)

  • Average Rating: 4.46/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Anyscale (+4.14%) - Among all products in this category, Anyscale recorded the largest rating increase compared to last month

Last updated: September 01, 2026

How Does G2 Rank Data Science and Machine Learning Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 14,400+ Authentic Reviews
  • 1,682+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for Data Science and Machine Learning Platforms

G2 Grid® for Data Science and Machine Learning Platforms plotting products by satisfaction and market presence

Highlighted products: Databricks, SAS Viya, Gemini Enterprise Agent Platform, Dataiku, Alteryx, IBM watsonx.ai, Deep Learning VM Image, and Google Cloud AI Hub.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-science-and-machine-learning-platforms/grids.json?focus%5B%5D=databricks&focus%5B%5D=sas-sas-viya&focus%5B%5D=gemini-enterprise-agent-platform&focus%5B%5D=dataiku&focus%5B%5D=alteryx&focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=deep-learning-vm-image&focus%5B%5D=google-cloud-ai-hub&segment=enterprise)

Snowflake

Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. The era of enterprise AI is here. Learn more at snowflake.com (NYSE: SNOW).

Average Rating: 4.6/5.0

Total Reviews: 713

How Do G2 Users Rate Snowflake?

  • Application: 9.2/10 (Category avg: 8.5/10)
  • Managed Service: 9.0/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Snowflake?

  • Seller: Snowflake, Inc.
  • Company Website:
  • Year Founded: 2012
  • HQ Location: 135 Constitution Drive, Menlo Park CA
  • Twitter: @SnowflakeDB
    278 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    12,574 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 45% Medium, 43% Large

What Do G2 Reviewers Say About Snowflake?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Snowflake, which simplifies data sharing and enhances productivity across teams.
  • Users value the reliable features and user-friendly interface of Snowflake, enhancing data management and analytics efficiency.
  • Users value the seamless scalability of Snowflake, enabling efficient handling of large datasets and workload changes without performance loss.
  • Users value the fast and efficient data processing capabilities of Snowflake, enhancing their analysis experience significantly.
Cons
  • Users highlight the high costs of Snowflake, making it less accessible for smaller businesses with limited budgets.
  • Users find feature limitations in Snowflake, such as lack of code blocks and restricted permissions, frustrating.
  • Users often struggle with high costs due to unoptimized queries and inadequate cost control measures in Snowflake.
  • Users find the cost structure challenging, requiring time to optimize for efficient use of Snowflake.
  • Users find Snowflake's limited features in dynamic scripts and monitoring hinder flexibility and usability.

What Are Recent G2 Reviews of Snowflake?

What Are G2 Users Discussing About Snowflake?

Teradata Autonomous Knowledge Platform

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

Average Rating: 4.3/5.0

Total Reviews: 354

How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.9/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Teradata Autonomous Knowledge Platform?

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 69% Large, 22% Medium

What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

AI-generated summary from verified user reviews

Pros
  • Users highlight the extreme performance of Teradata Autonomous Knowledge Platform, emphasizing its speed in processing large data volumes.
  • Users value the high performance and scalability of Teradata for handling complex queries and data integration.
  • Users value the scalability of Teradata Autonomous Knowledge Platform, seamlessly integrating and managing vast data resources efficiently.
  • Users commend the extreme performance of Teradata, highlighting its speed in processing large datasets seamlessly.
  • Users value the fast processing of large datasets in Teradata, appreciating its stability and integration capabilities.
Cons
  • Users identify a steep learning curve for Teradata Autonomous Knowledge Platform, hindering new user adaptation and productivity.
  • Users find the steep learning curve of Teradata Autonomous Knowledge Platform challenging, especially for those less technically inclined.
  • Users find the complexity of the Teradata platform challenging, especially for non-technical users and new adopters.
  • Users struggle with the cost transparency of Teradata Autonomous Knowledge Platform, needing close management to avoid issues.
  • Users express concerns about the high cost of the Teradata Autonomous Knowledge Platform, highlighting affordability issues.

What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

IBM Decision Optimization

IBM Decision Optimization is a family of prescriptive analytics products that combines mathematical and AI techniques to help with business decision-making including operational, tactical and strategic planning and scheduling use cases. The solutions enable business decision-makers to choose the optimal course of action from millions of alternatives when faced with decisions that involve multiple variables, trade-off possibilities and complex constraints. The solution incorporates powerful optimization solvers namely CPLEX Optimizer and CP Optimizer to solve the breadth of optimization problems including mathematical and constraint programming and constraint-based scheduling models. Learn more about this portfolio here https://www.ibm.com/analytics/decision-optimization IBM ILOG CPLEX Optimization Studio is one of the products within the IBM Decision Optimization portfolio. Organizations across industries are using IBM ILOG CPLEX Optimization Studio to drive operational efficiency and generate significant ROI by optimizing planning, scheduling, pricing and other business decisions. The offering provides users the flexibility to develop optimization models either using general programming language APIs like Python, Java, or using Optimization Programming Language (OPL). The powerful CPLEX optimization engines can deliver the power necessary to solve very large, real- world optimization problems at the speed required for today’s interactive decision optimization applications. Learn more about this product here - https://www.ibm.com/products/ilog-cplex-optimization-studio IBM Decision Optimization is also included within Watson Studio Premium for Cloud Pak for Data to enable data science teams to capitalize on the power of prescriptive analytics and build innovative solutions using a combination of techniques like machine learning and optimization. Data science teams can easily demonstrate business value of optimization by leveraging tools like visual dashboards & modeling assistant to quickly build models, test/evaluate multiple scenarios, solve using powerful optimization engines and deploy the models easily . IBM Decision Optimization solutions bring more than 30 years of experience in the field and is a proven optimization technology and organizations across industries are using IBM Decision Optimization solutions to run their mission-critical decision-making applications and have benefited by way of reduction in operating costs, increase in revenue and accelerated time to value.

Average Rating: 4.5/5.0

Total Reviews: 35

How Do G2 Users Rate IBM Decision Optimization?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.3/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Decision Optimization?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 59% Large, 22% Small

What Are Recent G2 Reviews of IBM Decision Optimization?

What Are G2 Users Discussing About IBM Decision Optimization?

Altair AI Studio

Altair AI Studio (formerly RapidMiner Studio) is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an organization. Altair AI Studio includes: - Full generative AI functionality with access to hundreds of large language models (LLMs). - Intuitive and powerful drag-and-drop canvases that give users code-like control without complexity. - Award-winning auto ML with automated clustering, predictive modeling, feature engineering, and time series forecasting. - Data connectivity, exploration, and preparation. - Deploy and manage AI projects and models at enterprise scale. - Collaborate with team members in the same environment without having to worry about overwriting each other's work. - Unify the entire data science lifecycle from data exploration and machine learning to model operations and visualization and deploy in the cloud. Altair AI Studio helps users make powerful insights accessible to the entire organization and can scale seamlessly for users and enterprises. Altair AI studio enables organizations to derive significant value from AI with minimal cost and operational impact.

Average Rating: 4.6/5.0

Total Reviews: 506

How Do G2 Users Rate Altair AI Studio?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.5/10 (Category avg: 8.6/10)

Who Is the Company Behind Altair AI Studio?

  • Seller: Altair
  • Company Website:
  • Year Founded: 1985
  • HQ Location: Troy, MI
  • LinkedIn® Page: www.linkedin.com
    2,630 employees on LinkedIn®
  • Ownership: NASDAQ:ALTR

Who Uses This Product?

  • Who Uses This: Student, Professor
  • Top Industries: Higher Education, Education Management
  • Company Size: 42% Small, 31% Large

What Do G2 Reviewers Say About Altair AI Studio?

AI-generated summary from verified user reviews

Pros
  • Users praise the ease of use of Altair AI Studio, finding its interface intuitive and beneficial for data tasks.
  • Users value the no-code machine learning capabilities of Altair AI Studio, facilitating easy model creation and analysis.
  • Users value the seamless AI integration of Altair AI Studio, enhancing decision-making and improving efficiency across organizations.
  • Users appreciate the advanced machine learning and data analytics in Altair AI Studio for smarter decision-making and efficiency.
  • Users value the automation capabilities of Altair AI Studio, enhancing efficiency in data processing and decision making.
Cons
  • Users find the complexity of Altair AI Studio challenging, particularly with language support and integrating legacy systems.
  • Users experience slower performance when handling large datasets in Altair AI Studio, affecting their efficiency and experience.
  • Users experience slow performance when handling large datasets, leading to slowdowns or freezing during usage.
  • Users find the complexity issues of Altair AI Studio frustrating, especially due to limited support resources.
  • Users find the complex usage of Altair AI Studio challenging, especially due to limited documentation and steep learning curve.

What Are Recent G2 Reviews of Altair AI Studio?

What Are G2 Users Discussing About Altair AI Studio?

TensorFlow

TensorFlow is an open-source machine learning library developed by the Google Brain Team, designed to facilitate the creation, training, and deployment of machine learning models across various platforms. It provides a comprehensive ecosystem that supports tasks ranging from simple data flow graphs to complex neural networks, enabling developers and researchers to build and deploy machine learning applications efficiently. Key Features and Functionality: - Flexible Architecture: TensorFlow's architecture allows for deployment across multiple platforms, including CPUs, GPUs, and TPUs, and supports various operating systems such as Linux, macOS, Windows, Android, and JavaScript. - Multiple Language Support: While primarily offering a Python API, TensorFlow also provides support for other languages, including C++, Java, and JavaScript, catering to a diverse developer community. - High-Level APIs: TensorFlow includes high-level APIs like Keras, which simplify the process of building and training models, making machine learning more accessible to beginners and efficient for experts. - Eager Execution: This feature allows for immediate evaluation of operations, facilitating intuitive debugging and dynamic graph building. - Distributed Computing: TensorFlow supports distributed training, enabling the scaling of machine learning models across multiple devices and servers without significant code modifications. Primary Value and Solutions Provided: TensorFlow addresses the challenges of developing and deploying machine learning models by offering a unified, scalable, and flexible platform. It streamlines the workflow from model conception to deployment, reducing the complexity associated with machine learning projects. By supporting a wide range of platforms and languages, TensorFlow empowers users to implement machine learning solutions in diverse environments, from research labs to production systems. Its comprehensive suite of tools and libraries accelerates the development process, fosters innovation, and enables the creation of sophisticated models that can tackle real-world problems effectively.

Average Rating: 4.5/5.0

Total Reviews: 136

How Do G2 Users Rate TensorFlow?

  • Application: 8.7/10 (Category avg: 8.5/10)
  • Managed Service: 8.5/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind TensorFlow?

  • Seller: TensorFlow
  • Year Founded: 2016
  • HQ Location: Centre Urbain Nord, TN
  • Twitter: @TensorFlow
    377,398 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Senior Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 51% Small, 26% Medium

What Do G2 Reviewers Say About TensorFlow?

AI-generated summary from verified user reviews

Pros
  • Users celebrate the flexibility and power of TensorFlow, enabling complex machine learning projects with ease.
  • Users praise the end-to-end AI integration of TensorFlow, which enhances project efficiency and flexibility across platforms.
  • Users appreciate the ease of use of TensorFlow, benefiting from strong support and comprehensive guides for model training.
  • Users appreciate the model variety in TensorFlow, enabling efficient and versatile machine learning across different platforms.
  • Users appreciate the scalability of TensorFlow, enabling efficient distributed training across various hardware platforms.
Cons
  • Users find the steep learning curve of TensorFlow difficult, requiring significant time and effort to master.
  • Users find TensorFlow complex and hard to learn, especially when debugging or converting models for embedded applications.
  • Users find the difficult learning curve of TensorFlow frustrating, especially when dealing with high-level Keras and deprecated APIs.
  • Users find error handling frustrating due to complex messages and difficult debugging processes, especially for beginners.
  • Users experience slow performance with TensorFlow, especially when executing complicated models and training larger frameworks.

What Are Recent G2 Reviews of TensorFlow?

What Are G2 Users Discussing About TensorFlow?

Posit Team

Posit is a Public Benefit Corporation building open-source software and an enterprise data science platform. We created the RStudio IDE, Shiny, Positron, and Quarto — tools used by millions of data scientists, machine learning engineers, and researchers worldwide, including teams at 25% of the Fortune Global 100. Our commercial products help organizations put those tools into production: Posit Workbench provides centralized development environments supporting Positron, RStudio, VS Code, and Jupyter; Posit Connect handles publishing and deployment for Shiny, AI applications, Streamlit, Dash, FastAPI, Flask, Bokeh, and more; and Posit Package Manager provides security-compliant package management for R and Python.

Average Rating: 4.5/5.0

Total Reviews: 568

How Do G2 Users Rate Posit Team?

  • Application: 8.4/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Posit Team?

  • Seller: Posit
  • Year Founded: 2009
  • HQ Location: Boston, US
  • Twitter: @posit_pbc
    120,874 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    441 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Research Assistant, Graduate Research Assistant
  • Top Industries: Higher Education, Information Technology and Services
  • Company Size: 49% Large, 26% Medium

What Do G2 Reviewers Say About Posit Team?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Posit Team, simplifying data analysis workflows and enhancing productivity.
  • Users praise Posit for its reliable performance and seamless integrations, enhancing productivity and simplifying workflows.
  • Users value Posit's commitment to open source software, enhancing productivity and integration with R programming.
  • Users appreciate the responsive and reliable customer support of Posit Team, enhancing their overall experience and productivity.
  • Users appreciate the easy integrations of Posit Team, enhancing their workflows with seamless compatibility with multiple tools.
Cons
  • Users experience slow performance with large datasets, which disrupts workflow and demands higher system requirements.
  • Users face a steep learning curve with Posit Team, making initial usage and advanced features challenging.
  • Users report performance issues with Posit Team, particularly during use with larger datasets and frequent crashes.
  • Users report a steep learning curve with Posit Team, making initial setup and advanced features challenging for newcomers.
  • Users face lagging performance with Posit Team, especially when handling large datasets, impacting overall productivity.

What Are Recent G2 Reviews of Posit Team?

What Are G2 Users Discussing About Posit Team?

Domo

Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI across their business. Built for enterprises, Domo works with existing cloud data platforms such as Snowflake, BigQuery, and Databricks to help teams turn governed data into AI-powered agents, apps, workflows, and analytics. Domo is built on three layers. The data foundation connects and governs data across cloud data platforms and business systems. The activation layer enables organizations to build AI agents, apps, workflows, automations, and dashboards on top of that foundation. The distribution layer delivers intelligence where work happens through embedded apps, mobile, dashboards, and AI assistants using Model Context Protocol (MCP). Governance underpins every layer, helping organizations scale AI and data products with security and trust. Key capabilities include: - Connecting and governing data across cloud data platforms and enterprise applications. - Building AI agents, apps, workflows, automations, dashboards, and analytics. - Delivering data and AI through dashboards, embedded apps, AI assistants, and AI agents. - Supporting both low-code and pro-code development for business and technical teams. - Applying governance, security, and access controls across data and AI. Organizations use Domo for AI agents, apps, and workflows, as well as business intelligence, operational analytics, embedded analytics, and executive reporting. By combining governed data, AI activation, app development, and distribution in a single platform, Domo helps organizations build and scale trusted data products across the enterprise.

Average Rating: 4.3/5.0

Total Reviews: 1,069

How Do G2 Users Rate Domo?

  • Application: 5.9/10 (Category avg: 8.5/10)
  • Managed Service: 6.4/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind Domo?

  • Seller: Domo
  • Company Website:
  • Year Founded: 2010
  • HQ Location: American Fork, UT
  • Twitter: @Domotalk
    63,513 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,288 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Business Analyst
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 50% Medium, 28% Large

What Do G2 Reviewers Say About Domo?

AI-generated summary from verified user reviews

Pros
  • Users find Domo's ease of use and intuitive design invaluable for managing data efficiently and effectively.
  • Users value the flexible and user-friendly data visualization capabilities of Domo, enhancing their data analysis experience significantly.
  • Users find Domo's intuitive design empowering, facilitating easy access and effective data visualization for all skill levels.
  • Users praise Domo for its easy integrations, streamlining data management and enhancing real-time collaboration across various platforms.
  • Users value Domo's seamless integration capabilities, enabling efficient data management and real-time insights from various sources.
Cons
  • Users find the learning curve steep, often needing dedicated resources to manage updates and functionalities effectively.
  • Users report missing features in Domo, including flexibility in pivot charts and dynamic column options.
  • Users face significant data management issues with Domo, including unreliable connectors and challenging reporting functionality.
  • Users find Domo expensive, especially with drastic price increases that strain budgets and erode client trust.
  • Users find Domo's complexity hinders flexibility and speed in dataset management, making changes challenging and time-consuming.

What Are Recent G2 Reviews of Domo?

What Are G2 Users Discussing About Domo?

KNIME

KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice.

Average Rating: 4.5/5.0

Total Reviews: 117

How Do G2 Users Rate KNIME?

  • Application: 8.5/10 (Category avg: 8.5/10)
  • Managed Service: 7.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.1/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.2/10 (Category avg: 8.6/10)

Who Is the Company Behind KNIME?

  • Seller: KNIME
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Zurich, Switzerland
  • Twitter: @knime
    7,998 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    244 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services, Higher Education
  • Company Size: 39% Large, 34% Medium

What Do G2 Reviewers Say About KNIME?

AI-generated summary from verified user reviews

Pros
  • Users find KNIME's ease of use enhances productivity, enabling even non-technical individuals to build workflows effortlessly.
  • Users find KNIME's coding ease remarkable, enabling effortless workflows without requiring extensive technical skills.
  • Users find KNIME to be an easy-to-learn platform, enabling quick workflow creation without coding skills.
  • Users find KNIME easy to learn and start delivering results, thanks to its intuitive visual workflow interface.
  • Users love the easy and intuitive data visualization capabilities of KNIME, enhancing understanding and communication of data insights.
Cons
  • Users find the initial learning curve challenging, especially for those unfamiliar with data science concepts and visual programming.
  • Users face memory usage issues with KNIME, leading to slow performance, especially with larger files and operations.
  • Users report storage limitations with KNIME, leading to performance issues and difficulties with large datasets.
  • Users note that data management issues hinder their experience, especially with file handling and certain databases.
  • Users find the lack of learning resources for KNIME to be a significant barrier to effective usage.

What Are Recent G2 Reviews of KNIME?

What Are G2 Users Discussing About KNIME?

Anaconda Core

Anaconda is built to advance AI with open source at scale, giving builders and organizations the confidence to increase productivity, and save time, spend and risk associated with open source. 95% of the Fortune 500 including Panasonic, AmTrust, Booz Allen Hamilton and over 50 million users rely on the value The Anaconda Platform delivers through a centralized approach to sourcing, securing, building, and deploying AI. With 21 billion downloads and growing, Anaconda has established itself as the gold standard for Python, data science, and AI and the enterprise-ready solution of choice for AI innovation. Anaconda is available across hybrid AI environments and cloud platforms such as AWS, Microsoft Azure, Databricks, Snowflake and more with backing from world-class investors including Insight Partners. Learn more at https://www.anaconda.com.

Average Rating: 4.5/5.0

Total Reviews: 234

How Do G2 Users Rate Anaconda Core?

  • Application: 8.9/10 (Category avg: 8.5/10)
  • Managed Service: 8.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.5/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Anaconda Core?

  • Seller: Anaconda, Inc.
  • Year Founded: 2012
  • HQ Location: Austin, Texas
  • Twitter: @anacondainc
    83,629 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    580 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 38% Small, 25% Large

What Do G2 Reviewers Say About Anaconda Core?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Anaconda Core, making package management and installation simple across platforms.
  • Users find the setup ease of Anaconda Core remarkable, making project initiation and package management simple and efficient.
  • Users value the efficiency of Anaconda Core, enhancing productivity and simplifying the workflow for data science projects.
  • Users appreciate the intuitive design of Anaconda Core, facilitating efficient project management and easy navigation.
  • Users enjoy the coding ease provided by Anaconda Core, simplifying package management and enhancing productivity in data science.
Cons
  • Users face data management issues with Anaconda Core, including large installations and challenges with backup and integration.
  • Users experience slow performance with Anaconda Core, particularly during installation and on older hardware, affecting usability.
  • Users find the limited features of Anaconda Core insufficient, impacting their ability to fully utilize the platform.
  • Users find the limited features of Anaconda Core hinder their experience and reduce functionality compared to competitors.
  • Users report a limited storage concern, finding the Anaconda Core installation size cumbersome for their devices.

What Are Recent G2 Reviews of Anaconda Core?

What Are G2 Users Discussing About Anaconda Core?

Red Hat OpenShift Data Science

Red Hat® OpenShift® AI is a flexible, scalable artificial intelligence (AI) and machine learning (ML) platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid cloud environments. Built using open source technologies, OpenShift AI provides trusted, operationally consistent capabilities for teams to experiment, serve models, and deliver innovative apps.

Average Rating: 4.4/5.0

Total Reviews: 33

How Do G2 Users Rate Red Hat OpenShift Data Science?

  • Application: 8.7/10 (Category avg: 8.5/10)
  • Managed Service: 8.8/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.7/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Red Hat OpenShift Data Science?

  • Seller: Red Hat
  • Year Founded: 1993
  • HQ Location: Raleigh, NC
  • Twitter: @RedHat
    300,769 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    19,487 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Market Research, Marketing and Advertising
  • Company Size: 42% Large, 39% Medium

What Are Recent G2 Reviews of Red Hat OpenShift Data Science?

What Are G2 Users Discussing About Red Hat OpenShift Data Science?

IBM SPSS Modeler

The IBM SPSS Modeler is a leading, visual data science and machine learning solution. It helps enterprises accelerate time to value and desired outcome by speeding the operational tasks for data scientists. Leading organizations worldwide rely on IBM for data discovery, predictive analytics, model management and deployment, and machine learning to monetize data assets. The IBM SPSS Modeler empowers organizations to tap data assets and modern applications with complete, out-of-box algorithms and models, suited for hybrid, multi-cloud environments with robust governance and security posture. • Take advantage of open source based innovation including R or Python • Empower data scientists of all skills – programmatic and visual • Exploit multi-cloud approach - on-prem, public or private clouds • Start small and scale to enterprise-wide, governed approach

Average Rating: 4.0/5.0

Total Reviews: 128

How Do G2 Users Rate IBM SPSS Modeler?

  • Application: 7.5/10 (Category avg: 8.5/10)
  • Managed Service: 7.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 6.4/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM SPSS Modeler?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Top Industries: Higher Education, Education Management
  • Company Size: 53% Large, 24% Medium

What Do G2 Reviewers Say About IBM SPSS Modeler?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the robust analytical modeling capabilities of IBM SPSS Modeler, enhancing data manipulation and preparation efficiency.
  • Users value the seamless data manipulation and robust analytical modeling capabilities of IBM SPSS Modeler for BI applications.
  • Users value the seamless data access in IBM SPSS Modeler, enhancing their ability to work with various datasets effectively.
  • Users value the seamless data manipulation capabilities of IBM SPSS Modeler, enhancing efficiency in BI tools integration.
  • Users value the seamless data visualization capabilities of IBM SPSS Modeler, enhancing their analytical precision and efficiency.
Cons
  • Users find the expensive licensing costs of IBM SPSS Modeler to be a significant drawback for individual use.
  • Users find the licensing costs prohibitive, making IBM SPSS Modeler an expensive choice for many.

What Are Recent G2 Reviews of IBM SPSS Modeler?

What Are G2 Users Discussing About IBM SPSS Modeler?

DataRobot

DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. This platform maximizes business value by delivering AI at scale and continuously optimizing performance over time. The company’s proven combination of cutting edge software and world-class AI implementation, training, and support services, empowers any organization – regardless of size, industry, or resources – to drive better business outcomes with AI.

Average Rating: 4.4/5.0

Total Reviews: 41

How Do G2 Users Rate DataRobot?

  • Application: 5.0/10 (Category avg: 8.5/10)
  • Managed Service: 1.7/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.0/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.7/10 (Category avg: 8.6/10)

Who Is the Company Behind DataRobot?

  • Seller: DataRobot
  • Year Founded: 2012
  • HQ Location: Boston, Massachusetts
  • Twitter: @DataRobot
    19,225 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    886 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 41% Medium, 41% Small

What Are Recent G2 Reviews of DataRobot?

IBM Cloud Pak for Data

IBM Cloud Pak® for Data is a fully integrated data and AI platform that modernizes how businesses collect, organize and analyze data, forming the foundation to infuse AI across their organization. Running on Red Hat OpenShift and available on any cloud, this unified platform helps companies automate the end-to-end AI lifecycle. The intelligent data fabric in IBM Cloud Pak for Data enables automated distributed queries at scale without data movement; automated discovery and understanding of business-ready data; automated universal privacy and usage policies across the data ecosystem; and optimized model training, accuracy and explainability. View the demo: https://mediacenter.ibm.com/media/1_je41fqqz. The platform delivers on the below use cases: • Data access and availability – Eliminate data silos and simplify your data landscape to enable faster, cost-effective extraction of value from your data. • Data quality and governance - Apply governance solutions and methodologies to deliver trusted, business data. • Data privacy and security - Fully understand and manage sensitive data with a pervasive privacy framework. • ModelOps - Automate the AI lifecycle and synchronize application and model pipelines to scale AI deployments. • AI governance – Ensure your AI is transparent, compliant and trustworthy with greater visibility into model development, with capabilities such as explainable AI, model risk management and bias detection. • AI for Financial Operations - Automate and integrate planning across your organization, from financial planning & analysis to workforce planning, sales forecasting and supply chain planning. • AI for Customer care - Reduce time to resolution, decrease call volume and increase customer satisfaction. IBM Watson Assistant (WA) can provide AI-powered automated assistance and enable human agents to better handle inquiries. IBM Watson Discovery (WD) complements Watson Assistant and can help unlock insights from complex business content. Discover IBM Cloud Pak for Data Industry Accelerators: https://dataplatform.cloud.ibm.com/gallery?context=cpdaas See a case study: https://mediacenter.ibm.com/media/1_sr6lx8sz Try at no-cost: http://ibm.biz/dataplatformtrial

Average Rating: 4.3/5.0

Total Reviews: 71

How Do G2 Users Rate IBM Cloud Pak for Data?

  • Application: 8.8/10 (Category avg: 8.5/10)
  • Managed Service: 8.5/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 9.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.6/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Cloud Pak for Data?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • Twitter: @IBMSecurity
    74,660 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 52% Large, 27% Small

What Are Recent G2 Reviews of IBM Cloud Pak for Data?

Hex

Hex is the world’s favorite AI Analytics platform. With Hex, anyone can explore data using natural language, with or without code, all on trusted context, in one AI-powered platform. Get started now > https://app.hex.tech/signup?source=g2 Get a demo > https://hex.tech/request-a-demo/?source=g2

Average Rating: 4.5/5.0

Total Reviews: 402

How Do G2 Users Rate Hex?

  • Application: 6.9/10 (Category avg: 8.5/10)
  • Managed Service: 6.8/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.1/10 (Category avg: 8.3/10)
  • Ease of Admin: 9.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Hex?

  • Seller: Hex Tech
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco, US
  • Twitter: @_hex_tech
    6,982 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    280 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Data Scientist
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 53% Medium, 22% Small

What Do G2 Reviewers Say About Hex?

AI-generated summary from verified user reviews

Pros
  • Users find Hex to be user-friendly, highlighting its seamless integrations and fast implementation as major advantages.
  • Users love the seamless integration of SQL with Python, enhancing their analytical capabilities in Hex effortlessly.
  • Users appreciate the seamless data management capabilities of Hex, enabling effortless integration and collaboration.
  • Users value the effortless integration of SQL and Python in Hex, enhancing data analysis and visualization capabilities.
  • Users appreciate the seamless data analysis and reporting capabilities of Hex, enhancing collaboration and interactivity.
Cons
  • Users criticize the limited features of Hex, noting insufficient capabilities compared to standard BI tools like Tableau.
  • Users find the missing features in Hex frustrating, desiring better data visualization and result management capabilities.
  • Users find Hex lacking features, especially in dashboarding and advanced functionalities that impact usability and efficiency.
  • Users experience slow performance with Hex, especially within virtual machines and due to limited computational capacity.
  • Users often face data management issues with kernel failures and GPU integration, complicating their experience with Hex.

What Are Recent G2 Reviews of Hex?

What Are G2 Users Discussing About Hex?

Deepnote

Deepnote is a data workspace where agents and humans work together. It's designed to simplify data exploration, accelerate analysis, and quickly deliver actionable insights for you and your team. Unlike outdated tools such as Jupyter, Deepnote is built with the next decade in mind. Deepnote gives anyone working with data superpowers. It unifies your data workflow through an integrated semantic layer, preparing your data for advanced AI applications. You can also leverage our AI data copilot to chat with your data, create charts, write code, or turn your AI notebooks into fully-fledged data dashboards or apps. Combine data, SQL or Python code, and visualizations side-by-side on a flexible canvas - enhanced with cutting-edge AI reasoning models. 🤖 Analyze with AI • Generate code and visualizations by describing your goal. • Auto-write, run, and debug code with AI. • Move faster with context-aware AI suggestions. 🔗 Unify • Connect to 60+ data sources like BigQuery, Snowflake, and PostgreSQL. • Combine Python and SQL in one notebook. • Build reusable ETL, analytics, and metric modules. • Create a semantic layer with shared definitions and trusted metrics. ⚖️ Scale • Instantly boost compute power, more included than Colab. • Schedule jobs and get notified with fresh results. • Organize work in projects and folders for team clarity. • Manage workflows via REST API. 🚀 Launch • Turn notebooks into dashboards or data apps, natively or with Streamlit. • Let users explore data with interactive inputs. • Share secure, live apps in one click.

Average Rating: 4.5/5.0

Total Reviews: 382

How Do G2 Users Rate Deepnote?

  • Application: 8.0/10 (Category avg: 8.5/10)
  • Managed Service: 7.9/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.8/10 (Category avg: 8.6/10)

Who Is the Company Behind Deepnote?

  • Seller: Deepnote
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco , US
  • Twitter: @DeepnoteHQ
    5,239 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    21 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Data Analyst
  • Top Industries: Computer Software, Higher Education
  • Company Size: 67% Small, 25% Medium

What Do G2 Reviewers Say About Deepnote?

AI-generated summary from verified user reviews

Pros
  • Users find Deepnote's ease of use enhances collaboration and simplifies data analysis with its intuitive interface.
  • Users value the seamless collaboration capabilities of Deepnote, enhancing teamwork and efficiency in data projects.
  • Users value the real-time collaboration capabilities of Deepnote, enhancing teamwork and efficiency in analytics processes.
  • Users value the easy integrations in Deepnote, enabling faster development and seamless data management across platforms.
  • Users find data management effortless with Deepnote, benefiting from easy integrations and seamless analysis capabilities.
Cons
  • Users notice slow performance when handling large datasets, affecting analysis speed and user experience.
  • Users find the limited features of Deepnote restricts their ability to fully utilize its potential.
  • Users experience data management issues with slow performance and an unintuitive file management system, affecting usability.
  • Users experience lagging performance with Deepnote, particularly when processing large datasets, affecting efficiency during critical tasks.
  • Users face slow loading times in Deepnote, particularly with larger projects, which can hinder productivity and frustrate experiences.

What Are Recent G2 Reviews of Deepnote?

What Are G2 Users Discussing About Deepnote?